SYSTEM AND METHOD FOR WiFi POSITIONING

Abstract

An aspect of the invention provides instantaneous Wi-Fi positioning that is robust to outliar APs using a recursive centroid method. It estimates user position and uncertainty based on the current list of scanned APs. Another aspect of the invention provides a Wi-Fi navigation solution that estimates good Wi-Fi positions even in the areas of low AP density and further improves robustness to outliar APs. Wi-Fi navigation solution improves the estimate of instantaneous Wi-Fi positioning by using a 4-state Kalman filter, which models user dynamics. As a result, the uncertainty estimate of the Wi-Fi positions is accurately estimated, thereby, making it suitable for blending with GNSS.

Description

BACKGROUND[0001]The present invention relates to Wi-Fi based positioning systems, in particular, Wi-Fi based positioning systems for location based services.[0002]Location based services are an emerging area of mobile applications that leverages the ability of new devices to calculate their current geographic position and report that to a user or to a service. Some examples of these services include identifying a location of a person or an object in the context of entertainment, work, health or personal life.[0003]Wi-Fi is a mechanism that allows an electronic device to exchange data wirelessly over a computer network. Some technologies based on IEEE 802.11 standards that use Wi-Fi include Wireless Local Area Network (WLAN) and Wi-Fi direct. A Wi-Fi enabled device such as a smart phone, a personal computer, a tablet or a video game console can connect to a network resource such as the internet via a wireless network Access Point (AP). An AP or a hotspot has a range of about 20 meter...

AI Technical Summary

Benefits of technology

The present invention is a device that can receive signals from multiple access points and determine its location based on the distances between the device and each access point. The device can also compare the distances with pre-defined thresholds and determine a modified location if needed. The technical effect of this invention is to improve the accuracy and accuracy of location tracking for devices in wireless networks.

Problems solved by technology

GPS performs poorly in urban areas where buildings block the view of satellites, and it does not provide any coverage inside of buildings.

Wi-Fi hotspot triangulation is a commonly used method of determining location on modern smart phones, as GPS does not always work in urban locations and cell-tower positioning can be inaccurate.

The accuracy of Wi-Fi positioning is affected by accuracy of AP locations in the database, in addition to the low AP visibility.

This process inherently is error prone.

In some cases, there could be huge errors, for example, if there is an AP that moves around from place to place.

The possible signal fluctuations that may occur in the path of the received signal can increase errors and inaccuracies in the path of the user.

In certain cases, depending on the location from where the user reports it, the geometry may be poor, for example, if all the users report it from one location then it will be difficult to find that AP.

Furthermore, mobility of an AP can cause huge errors in locating that AP.

Therefore, if a mobile AP's reported location is unrelated to the current location then the user reporting this AP will get bad information and may cause position outliars.

As mobile APs proliferate, the problem is expected to become more severe.

When a user reports this AP to the database in order to get a Wi-Fi position, he gets bad information resulting in an outliar fix.

The problem of AP location being off from its current location may confuse the Wi-Fi positioning method, especially if there are very few APs detected and their location is not accurate.

Another common problem is non-uniform densities of the AP in an urban area.

Low densities will degrade the performance of the Wi-Fi positioning method.

Furthermore, during scanning process, all of the APs which are present may not be discovered.

Generally, on an average, only a percentage of the APs will be discovered, therefore, limiting the number of available APs.

Hence, low AP visibility is caused by low AP density in some parts and also fewer APs discovered during the scan process due to packet collisions, scan time limitations and high path loss, etc.

This is a slow process since the database has to wait for the inputs from multiple users on each AP.

Additionally, the database cannot remove moderate outliers, for example, an AP moving between home and office or between streets is difficult to classify as a distinct error.

However, it is not always desirable due to the cost involved and the hassle to download the database frequently on a user's smart phone or personal computer.

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